Kenneth Miller

Current Institution
Columbia University

Scholar: 1994

Awarded Institution
University of California, San Francisco


Research Interests

Neuronal Circuitry: Structure, Plasticity, and Function

My lab's interests focus on understanding the cerebral cortex. We use theoretical and computational methods, and theoretically motivated experimental methods, to unravel the circuitry of the cerebral cortex, the rules by which this circuitry develops or "self-organizes", and the computational functions of this circuitry.

One goal of the lab is to understand the role of activity-dependent, "correlation-based" mechanisms of synaptic plasticity in determining cortical structure and function. Under these mechanisms, synaptic change appears to follow a rule like that proposed by Hebb in 1949: a synapse is strengthened when pre- and postsynaptic activations are correlated. We have analyzed cortical development in the presence of such plasticity. One prominent feature of visual cortical development is the formation of ocular dominance columns. These are alternating patches of cortical cells that receive input only from the left eye or only from the right eye. The left- and right-eye inputs segregate, beginning from an initially intermixed condition, through an activity-dependent synaptic competition. We have predicted the conditions under which input neural activity will lead to such segregation, and the size of the resulting patches. Another feature of visual cortex is the tuning of the cells to respond to light-dark borders of a particular orientation. Our analysis revealed that the development of such orientation-selectivity can be explained by a correlation-based competition between ON-center and OFF-center inputs to the visual cortex, very much like the left-eye/right-eye competition that leads to ocular dominance column formation but in a different parameter regime. We are currently examining such issues as the joint development of orientation and ocular dominance, the effects on increased realism in our models of cortical circuitry and of learning rules, sensorimotor learning, and learning involving feedback as well as feedforward and intrinsic connections.

Another goal is to develop realistic and testable models of mature cortical circuitry. We have developed improved simple models of cortical excitatory cells and shown how these naturally account for the high variability of cortical responses. We are currently developing circuit models to explain basic features of visual cortical responses. Models of cortical cells and networks are constrained by our knowledge of cellular structure and function, the statistics of cortical connectivity, and the temporal and spatial structures of cortical responses both intracellular and extracellular. Model circuits that satisfy these constraints represent testable hypotheses as to the cortical circuitry underlying functional responses.

Finally, experimental methods for the study of the simultaneous activity of many neurons in visual cortex are being established, using the "tetrode" method of recording. These will serve both to inform and to test the models. Simultaneous recording from many neurons also provides a basis for other theoretical studies, such as the analysis of the cortical coding and representation of sensory information.